Data Analyst
📍 Location: Dallas, Texas, United States (Hybrid)
🏢 Industry: Financial Services
💼 Work Setting: Hybrid
Are you passionate about transforming data into strategic business assets and building modern, scalable data ecosystems? We are seeking an experienced Data Analytics and Data Engineering professional to lead the design, development, and implementation of enterprise data solutions that drive operational efficiency, risk management, and business intelligence.
In this role, you will help organizations modernize their data landscape by designing data platforms, engineering data products, and enabling advanced analytics capabilities. You will assess current-state environments, identify improvement opportunities, recommend future-state solutions, and implement robust data architectures that support data-driven decision-making.
Key responsibilities include defining data and analytics strategies, leading data modernization initiatives, designing scalable data pipelines and platforms, improving data governance and controls, and leveraging emerging technologies to enhance business processes. You will collaborate with cross-functional stakeholders, oversee project delivery, mentor team members, and contribute to thought leadership through innovative concepts, research, and industry-focused insights.
The ideal candidate will possess strong problem-solving skills, the ability to lead diverse teams, and a track record of delivering high-quality data and analytics solutions. Success in this role requires strong technical expertise, stakeholder management capabilities, and the ability to influence business and technology leaders while fostering long-term professional relationships.
Required Qualifications
- Bachelor's degree in Engineering, Computer Science, Business, Economics, Finance, Statistics, Analytics, or a related discipline with 5+ years of relevant experience; or Master's degree in a related field with 4+ years of relevant experience.
- Minimum 3 years of experience within financial services domains such as banking, capital markets, insurance, wealth management, or asset management.
- At least 3 years of experience in one or more of the following areas:
- Data Architecture and Engineering
- Cloud Data Modernization
- Data Products
- Data Mesh
- Data Fabric
- Big Data Platforms
- Event-Driven Architectures
- Experience with traditional data management and architecture solutions, including:
- Master Data Management (MDM)
- Operational Analytics
- Customer Data Platforms/Hubs
- Data Warehousing
- Hands-on experience with modern data platforms and technologies such as:
- Cloud platforms (AWS, Azure, or GCP)
- Snowflake
- Databricks
- Distributed database technologies
- Proven expertise in architecting and implementing:
- Enterprise data platforms
- Data warehouses
- Streaming applications
- Data ingestion frameworks
- Data storage architectures
- Data integration solutions
- Experience in one or more of the following technology categories:
- Relational Databases (SQL Server, Oracle, MySQL, PostgreSQL)
- MPP/Data Warehouse Platforms (Redshift, Synapse, Teradata, Vertica, Netezza)
- NoSQL Databases (MongoDB, DynamoDB, Cassandra, Neo4j, Elasticsearch)
- Streaming Technologies (Kafka, Spark Streaming, Confluent, Storm)
- DevOps & Automation Tools (GitHub, Kubernetes, Jenkins, Terraform)
- Data Modeling methodologies (Data Vault, Star Schema, Snowflake Schema, Canonical Models)